Hybrid Connectionist-Structural Acoustical Modeling In The Atros System

In this paper, we introduce several hybrid connectionist-structural acoustic models for contextindependent phone-like units in the atros recognition system. The structural part of the acoustic models has been modeled with Markov chains, and a multilayer perceptron (or a committee of multilayer perceptrons) is used to estimate the emission probabilities of the Markov chains. We compare the recognition performance attained by these models with the performance obtained by classical continuous density hidden Markov models on a semantic restricted task. 1 Introduction Acoustic phonetic-decoding for continuous speech recognition is an open problem in speech research, because the nal performance of an automatic speech recognition system greatly depends on the acoustic modeling quality. Hidden Markov models (HMMs) of phone-like units are the most popular option for modeling speech sounds. Under the statistical framework [1], the problem of speech recognition is to search for a word string ^ ..